---
title: Semantic Chunking
---

Semantic chunking is a method of splitting documents into smaller chunks by analyzing semantic similarity between text segments using embeddings. It uses the chonkie library to identify natural breakpoints where the semantic meaning changes significantly, based on a configurable similarity threshold. This helps preserve context and meaning better than fixed-size chunking by ensuring semantically related content stays together in the same chunk, while splitting occurs at meaningful topic transitions.

## Code

```python
import asyncio
from agno.agent import Agent
from agno.knowledge.chunking.semantic import SemanticChunking
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.pdf_reader import PDFReader
from agno.vectordb.pgvector import PgVector

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"

knowledge = Knowledge(
    vector_db=PgVector(table_name="recipes_semantic_chunking", db_url=db_url),
)
asyncio.run(knowledge.add_content_async(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
    reader=PDFReader(
        name="Semantic Chunking Reader",
        chunking_strategy=SemanticChunking(similarity_threshold=0.5),
    ),
))

agent = Agent(
    knowledge=knowledge,
    search_knowledge=True,
)

agent.print_response("How to make Thai curry?", markdown=True)

```
## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install libraries">
    ```bash
    pip install -U sqlalchemy psycopg pgvector agno chonkie
    ```
  </Step>


    <Snippet file="run-pgvector-step.mdx" />


  <Step title="Run Agent">
    <CodeGroup>
    ```bash Mac
    python cookbook/knowledge/chunking/semantic_chunking.py
    ```

    ```bash Windows
    python cookbook/knowledge/chunking/semantic_chunking.py
    ```
    </CodeGroup>
  </Step>
</Steps>



## Semantic Chunking Params

<Snippet file="chunking-semantic.mdx" />
